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Density-Based Clustering

Domino Data Lab

DECEMBER 2, 2020

Due to its importance in both theory and applications, this algorithm is one of three algorithms awarded the Test of Time Award at the KDD conference in 2014. To test out DBSCAN, I’m going to use a dataset consisting of annual customer data for a wholesale distributor. Application.

Metrics

Metrics KDD Testing Machine Learning

Using Empirical Bayes to approximate posteriors for large "black box" estimators

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

For an introduction to Empirical Bayes, see the paper [3] by Brad Efron (with more in his book [4]). One way to check $f_theta$ is to gather test data and check whether the model fits the relationship between training and test data. Figure 4 shows the results of such a test. How exactly should we model $G$?

KDD

KDD Testing Machine Learning Modeling

Data Leaders Brief

Density-Based Clustering

Using Empirical Bayes to approximate posteriors for large "black box" estimators

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